ASSOCIATION FOR CONSUMER RESEARCH

Labovitz School of Business & Economics, University of Minnesota Duluth, 11 E. Superior Street, Suite 210, Duluth, MN 55802 Gender Differences in the Choice of Payment Method For Purchasing Durable Goods

Hyuncha Choe, Purdue University, Indiana S. J. Yoon, Purdue University, Indiana Dixie P. Johnson, Purdue University, Indiana

[to cite]:

Hyuncha Choe, S. J. Yoon, and Dixie P. Johnson (1991) ,"Gender Differences in the Choice of Payment Method For Purchasing

Durable Goods", in GCB - Gender and Consumer Behavior Volume 1, eds. Dr. Janeen Arnold Costa, Salt Lake City, UT :

Association for Consumer Research, Pages: 32-42.

[url]:

http://www.acrwebsite.org/volumes/15542/gender/v01/GCB-01

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Gender Differences in the Choice of Payment Method for Purchasing Durable Goods

Hyuncha Choe, Purdue University, Indiana S. J. Yoon, Purdue University, Indiana Dixie P. Johnson, Purdue University, Indiana

To examine the gender differences in the consumer payment behavior for purchasing durable goods, factors associated with the probability of using three kinds ofpayment methods - cash or check, credit cards, and consumer loans - were investigated with the data from 1983 Survey of Consumer Finance using binomiallogit analysis. Significant gender differences were found in the use of three alternative methods ofpayment. Three factors uniquely significant for female-headed households were household income, race, and household size. Only one factor, negative attitude towards credit, was uniquely significant for male-headed households.

INTRODUCTION

One of the fastest growing population sectors in the United States is the households headed by female. In 1987, 86 percent of single-parent households and 60 percent of single-person households were female-headed households (Crispell 1989). The financial status and spending behavior of female-headed households have become growing research areas because of their numbers and spending power (Crispell 1989; Exter 1990; Lino 1989; 1990; Shipp 1988). According to these studies, male- and female­headed households show different financial status and spending behavior. Female-headed households have an after-tax income that is less than half of male-headed households' and are more likely to have total expenditures that exceed their after-tax income (Lino 1989).

Since female-headed households face severe budget constraints more often than male-headed households, it is worth examining whether the female-headed households are more likely to use credit cards and consumer loans than the male­headed households. These kinds of payment systems allow consun1ers to buy goods and services without having funds available at the time of purchase. However, there is no empirical research concerning the sex differences in the

utilization of alternative payment methods in the context of durable goods purchases.

While consumers usually use cash, personal check, credit card or debit card to purchase goods and services, they may use consumer loans as well. Given the high ticket price of many consumer durables, the use of consumer loans is a viable alternative as a method of purchase.

Consumer durables, primarily consisting of motor vehicles, furniture, and household equipment, compose about 15% of all consumer expenditures. Considering an additional 11% of consumer expenditures on maintaining and operating consumer durables, the average household spends about 26% of its total budget on these durable goods (Winger & Frasca 1989).

Past research explaining the method of payment has focused on attributes of consumer payment systems (Hirschman 1981; 1982). The emphasis has been on the relationships between consumer purchasing behavior and method of payment (Feinberg 1986; Hirschman 1979; Hirschman, Alpert, and Srivastava 1980; Lindley, Rudolph, and Selby; 1989), focusing on the differences in the consumer purchasing behavior by credit cards and/or cash. However, no previous studies included consumer loans as an alternative payment system.

Therefore, the purpose of this study is to examine the gender differences in the consumer payment behavior for purchases of durable goods, using binomial logit analysis to identify the factors associated with the probability of using the various payment methods.

PREVIOUS RESEARCH ON METHOD OF PAYMENT

Almost all previous studies on the method of payment have focused on the characteristics of

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bank credit card users versus non-users (Jensen and Reynolds 1986; White 1975) and revolving users versus non-revolving users (Ethridge 1982; Mathews and Slocum 1969; Slocum and Mathews 1970; Soberon-Ferrer and Hatfield-Goldman 1988). However, Feinberg (1986), Hirschman (1980), Hirschman, et al. (1979), and Lindley, Rudolph, and Selby (1989) have studied the relationships bet\veen consumer purchasing behavior and method of payment system -- bank versus store-issued cards, cash versus credit card ­- and the probabilities of using an alternative payment system for retail purchasing.

Mathews and Slocum (1969) and Slocum and Mathews (1970), in their study of the effects of social class on the use of commercial bank credit cards, classified the credit card users as convenience users (i.e., non-revolvers) -- those who payoff the balance in full and use credit cards for transaction purposes -- and installment users (i.e., revolvers) -- those who pay a portion of the balance and use credit cards for financing needs. They found that the installment users tended to be members of the lower social classes and had a more favorable attitude toward purchasing consumer durable goods on credit. They also pointed out that the acceptability of purchasing goods and services on credit depended on social class. Ethridge(1982) and Soberon­Ferrer & Hatfield-Goldman (1988) reported similar results. Ethridge (1982), using the 1977 Consumer Credit Survey, found that revolvers of credit cards were more likely to use credit cards to purchase consumer durables. In the study of social class effect on the consumer credit card repayment behavior, Soberon-Ferrer & Hatfield­Goldman (1988) reported that social class, as well as assets and debts, was the most important variable affecting the likelihood of using credit cards for a revolving purpose. The consumers in the upper social class, with greater asset holdings and with less debt holdings, were less likely to use credit cards for revolving credit.

Using probit analysis, White (1975) attempted to predict the probability of using a credit card to measure the costs of making different transactions indirectly. Single males were found to be more likely to use credit cards (White 1975). White also found that the size of a transaction, as well as race, age, and size of outstanding credit card balance, was the most significant variable. Furthermore, the effect of the size of transaction

was negative on the probability of using a credit card (White 1975).

Bellenger et al. (1979) created life style profiles for credit oriented and cash oriented females and tested the relationships of demographic variables to credit orientation. In this research, they found that females who are liberal, convenience oriented, social, in higher income and education levels, aged between 25-54, and living in urban areas, are more likely to be credit oriented.

Credit card ownership was found to be the single most significant factor positively related to purchasing behavior (Hirschman 1979). Hirschman also found that credit card ownership was positively related to dollar volume of purchasing in the department store.

Feinberg (1986), using four controlled experiments, tested the hypotheses that credit card stimuli direct spending response and that the magnitude of the spending response would be affected by the presence or absence of a credit card. In these experiments, people appeared to be willing to spend more with credit cards, and credit card stimuli could enhance the magnitude, probability and decision time involved in spending. In a real spending situation, tipping was greater for equivalent check amounts when paid by credit card rather than cash (Feinberg 1986).

Jensen and Reynolds (1986) studied the differences in the use of open-end and closed-end credit of older households to investigate the effects of preretirement, using a sample from the 1977 Consumer Credit Survey. For open-end credit, income, education, being married, having a larger household, being a renter and being a female-headed household were positively associated with credit use. Having an unfavorable attitude towards credit was negatively associated with the probability of open-end credit use. Users of closed-end credit, so called installment credit, were more likely to be younger families with children, renters, married couples and families with a positive attitude towards credit. Older families with an average age over 65 were less likely to use closed-end credit.

From the analysis of whether or not a household used consumer installment credit, Sullivan and Warden (1986) found that households headed by single parents or young singles with a mortgage,

33

stable income and tvlo earners, had higher probability of using consumer installment credit. They also found that level of liquid assets and negative attitudes toward credit had negative effects on the probability of installment credit use.

Lindley, Rudolph, and Selby (1989), using probit analysis, examined the changes in consumer credit card possession and use behavior of tvlo samples of interviewed households between 1971 and 1983. Females were less likely than males to use credit cards for purchasing gasoline and furniture, while they were more likely to use credit cards for household goods and clothing (Lindley, et al. 1989). The probability of purchasing furniture, clothing or household goods with a credit card increased over time, holding other explanatory variables constant (Lindley, et al. 1989).

Based on previous research on the method of payment system and gender differences in consumers' payment method choice behavior, a null hypothesis may be constructed:

HI: There are no gender differences in the choice of three types of payment methods -- cash or check.. credit cards, and installment credit -- for purchasing durable goods.

MODEL AND METHOD OF ANALYSISMODEL

To test the hypothesis, an empirical model to be estimated was set up as:

p .. = f.1J J

(FINANCIALj,SOCIODEMOGRAPHICj,

AITITUDEj , COSTij )

where Pij is the probability of using the ith method of payment of jth household for purchasing durable goods, FINANCIALjis a vector of variables describing financial characteristics of the jth household,SOCIODEMOGRAPHICjis a vector of sociodemographic characteristics of the jth household, ATTITUDEj is a vector of attitudinal variables of the Jth household, and COSTi.j is the size of the jth household's durable goods transaction using ith payment system.

DATA

The data used in this study were taken from the 1983 Survey of Consumer Finances, sponsored by the Board of Governors of the Federal Reserve System and six other federal agencies. They collected data on the credit shopping and attitudes of consunlers toward credit use, and use of credit as reflected on their balance sheets (Avery, Elliehausen,& Canner 1984). This survey, from 3,824 families, is the most comprehensive collection of balance-sheet data since the 1962 Survey of Consumer Finances (Avery et al. 1984). The sample used for this study was limited to those who answered 'yes' for the question of recent purchase of durable goods over $5001.

Cases who expended more than $500 for home purchases usually categorized as housing expenditure, and for personal purposes such as travel and medical, etc. were excluded. Households reporting negative annual income as well as the high income subsample2 were also excluded to avoid biased results, leaving a total of 1,768 households for the present analysis. Of these, 1,479 households were headed by males and 289 households were headed by females.

VARIABLES

The dependent variable, method of purchase for durable goods, was divided into three modes of payment -- cash or check, c~edit cards, and consumer loan -- based on the answers for the question of the method of payment for purchasing durables that cost over $500. Each of three payment methods was assigned "l"if it was a mode chosen for the payment of the durable, and "Q"if it was not.

The independent variables used to explain the utilization of method of payment for purchasing durable goods were chosen based on the previous research and the previous discussion of the conceptual framework. Several financial (FINANCIAL·), sociodemographic (SOCIODEMbGRAPHICj) and attitudinal (ATTITUDEj) variables in addition to the amount of money spent on durable goods purchase (COSTij), were assumed to be related to the method of payment of durable goods purchases. Financial variables included in the model were current household pre-tax income, total financial assets, outstanding balances of mortgage debt, total consumer installment debt,

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total credit card debt, and home ownership. The households reporting 'zero' level of assets and debts were also included. Sociodemographic variables included in the model were gender, race, age, marital status, level of education of household head, and family size. General attitudes towards credit (negative and positive attitude) were also used to explain the use of alternative payment systems. Two separate dummy variables were created to identify the effects of negative and positive attitudes. The negative attitude towards credit was assigned "l"if the respondent answered that it is a bad idea for people to buy things on the installment plan, and "Q"if it is good in some ways, bad in others. The variable of positive attitude towards credit was also assigned in the same manner. All variables were continuous except for gender, race, marital status, attitude towards credit and home ownership. Non-whites, singles, and homeowners were coded as 1.

Analysis

Because of the nature of the dependent variable, a binomial logit analysis was used to test the empirical model and to estimate the coefficients of the explanatory variables. The maximum likelihood method is applied to estimate the logit coefficients. The likelihood ratio statistic is used to test the null hypothesis that all the parameters are zero. It is asymptotically distributed as chi­squared with 14 degrees of freedom. An informal goodness-of-fit index -- rho-squared -- that measures the fraction of an initial log likelihood value explained by the model is analogous to R2

used in regression (Ben-Akiva and Lerman 1989).

To test HI, three separate logit analysis models for each payment method were used to measure the effect of gender on the use of each payment method holding all other variables constant. The total sample was divided into two subsamples -­male-headed and female-headed households-­and three separate logit analyses for each subsample were also run. Male-headed and female-headed households also included single males and females, respectively.

Table 1 and 2 show use patterns of different payment methods and simple descriptive statistics of the sample by gender. Table 3 and 4 show the factors associated with the use of alternative payment methods by gender group as well as the

test results for gender differences in the choice of payment methods. To detect the interdependence of independent variables, simple correlation matrices were calculated; no multicorrelinearity was found.

RESULTS AND DISCUSSION

Table 1 shows a distribution of payn1ent methods for durables by gender of the household heads. It was found that female-headed households use cash or check in greater frequency than male-headed households to pay for the purchase of durables and that consumer loans are used more by male-headed households than by female-headed households. In all households, cash or checks was the most favored method of payment, followed by consumer loans and, credit cards.

Major financial and sociodemographic characteristics, including average expenditure for durable goods and attitude towards credit of sample households, are presented in Table 2. Student t-tests were performed to test the significance of differences in means between female-headed and male-headed households.

Eighty-four percent of total sample households were headed by males, while 16% of them were female-headed households. The majority of household heads (87%) were white. Seventy-eight percent of females were either divorced, widowed, or separated.

According to a gender-based comparison of the households, male-headed households were found to spend a greater amount of money on the purchase of durable goods.

The examination of financial variables revealed that male-headed households had more income, assets, and debts in the absolute amount than female-headed households.

The results of the logit analysis for the two gender groups are presented in Table 3. The overall patterns of significant factors were quite similar between gender within each of the three payment methods but not as much across the methods.

Cash or Checks

The significant factors associated with cash or

35

check use by both genders were total financial assets, installment debts, credit cards debts, home ownership, age, attitude toward credit, and amount spent on durable goods purchases. The less total financial assets, the more installment debts; and the more credit card debts they had, the TI10re likely households were to use cash or check.

Both male and female honleowners were less likely to use cash or check than male and female renters. The older the head, the less likely cash or check was used. While attitudinal variables were important as factors affecting the probability of using cash or check in male-headed households, they were not significant in female-headed households. Current household income had a significant negative effect on the use of cash or check in female-headed households while it was not significant in male-headed households. Race and household size were also significantly related to the probability of using cash or check only in female-headed households. Non-white females were more likely to use cash or check. And larger households headed by females were more likely to use cash or check.

Credit Cards

There were only a few factors related to credit card use as compared with other payment methods in both gender group. For male-headed households, education level and money spent on the purchase of durable goods had significant effects on the probability of using credit cards. Male-headed households with higher levels of education were less likely to use credit cards than male heads with a lower level of education. Unlike male-headed households, household income and credit card debts outstanding had significant effects on the probability of using credit cards in female-headed households. Specifically, the more household income and credit card debts they had, the less likely they were to use credit cards.

Consunler Loans

Of the financial variables affecting the use of consumer loans, household income, financial assets, installment debts, credit card debts, and home ownership were found to be significant variables for both male- and female-headed households. Household income was negatively

related to the use of consumer loans, while financial assets were positively related to it. As installment and credit card debts outstanding increased, households were less likely to use a consumer loan. Homeowners were more likely to use a consumer loan than renters. Among sociodemographic variables, age had a strong positive effect on the probability of using a consumer loan. Marital status and negative attitude toward credit had significant effects on the likelihood of male-headed households using a consumer loan, while they were not significant factors in fenlale-headed households. Male-heads who had negative attitudes toward credit were significantly less likely to use a consumer loan. Single male-heads were more likely to use a consumer loan. The probability of using a consumer loan was negatively significant when the head of household was a nonwhite female. The more money spent on durable purchases, the less likely households were to use a consumer loan. As household size increased, both male- and female-headed households were less likely to use a consumer loan.

To test the gender difference in the choice of alternative payment methods for purcha~ing

durable goods, the log likelihood index statistic (­2((log likelihood of male-headed households + log likelihood of female-headed households) - (log likelihood of total households))) was calculated. The test results are shown in Table 4. A chi­square distribution was used to test the log likelihood statistic. Table 4 indicated that there were significant gender differences in the choice of payment methods for purchasing durable goods among three alternative systems, thus HI was rejected.

SUMMARY AND CONCLUSION

We found that there were significant gender differences in the choice of payment methods for purchasing durable goods. As found in logit analysis results, the factors associated with the probability of using the various payment methods were different between male-headed and female­headed households.

In summary, only one variable, dollar amount of durable good purchase, came out the most significant across all three payment categories for both nlale-headed and female-headed households. The following factofs were significant fOf both

36

male and female-headed households in" at least two of the three categories of payment: level of financial assets, outstanding installment and credit card debt, home ownership, and age. Three factors uniquely significant for female headed households were household income, race, and household size. Only one factor was uniquely significant for male headed households: negative attitude towards credit. Mortgage debt, marital status, education, and positive attitude were not significant in at least two of the three payment methods for neither male nor female-headed households.

Household income had a strong negative impact on female headed households over all payment methods.

Race was not significant for male headed households but had a significant positive effect on cash purchase and a negative effect on probability of use of a conSumer loan for female headed households. Thus race was an important factor intluencing payment method for females. Either by choice or by market constraints, non-white females were less likely to use a consumer loan and more likely to pay cash.

Household size was significant for both females and males in decreasing the probability of use of a consumer loan. Controlling for household income, as household size increases, it may simply be more difficult to obtain a consumer loan. Women with larger families had a higher probability of paying cash.

Attitude toward credit was significant for male­headed households but not female-headed households. Males expressing positive attitudes toward credit were less likely to use cash, and males with a negative attitude were more likely to use cash and less likely to use a consumer loan.

The model had few significant predictions for payment by credit card. This may be, in part, because the credit card payment category included both revolvers and non-revolvers. The present study addresses the plastic/no plastic issue rather than separating out credit as a cash substitute (non-revolvers) from a revolving credit commitment as a choice of payment.

The differences found in predictive power between payment made by credit card and

consumer loan may involve the behavioral factors necessary to trigger a consumer loan. Putting a major ticket item on a credit card does not usually involve additional paper work at the time of purchase or trigger a credit check, the time delay involved in that check, and the potential for rejection.

1Respondents were asked if he/she had purchased a home, a vehicle, home improvement, addition, repairs, upkeep, or maintenance, large items for the household appliances and furnishings, recreation items, and personal expenses costing more than $500 within the previous year.

2A supplemental sample of 438 high-income households drawn from federal income tax files was included in the 1983. Survey of Consumer finances to provide better representation of the upper tail of the wealth distribution than that provided by most other surveys (Avery and Elliehausen 1988).

REFERENCES

Avery, R.B. and Elliehausen, G.E. (1988), 1983 Survey of Consumer Finances: Technical Manual and Codebook, Federal Reserve System.

Avery, R.B. and Elliehausen, Canner, G.B., and Gustafson, T.A. (1984), "Survey of Consumer Finances, 1983,"Federal Reserve Bulletin, 70(September),679-692.

Bellenger, D.N., Robertson, D.H., and Greenberg, B.A. (1979), "Female Attitudes Toward The Use of Credit Vs. Cash," Journal of Bank Research, Spring, 54-57.

Ben-Akiva, M and Lerman, S.R. (1989),Discrete Choice Analysis, Cambridge, Mass: The MIT Press.

Crispell, Diane (1989), "Women in Charge," American Demographics, September, 26-29.

Ethridge, Veree (1982), "Factors Related to Credit Card Users on Basis of Method of Repayment," Home Economics Research Journal, 10(3), 293-299.

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Exter, Thomas (1990), "Spending Money: Entertaining Singles," American Demographics, Au~ust, 6-7.

Feinberg, R.A. (1986), "Credit Cards as Spending Facilitating Stimuli: A Conditioning Interpretation,"Journal of Conswner Research, 13(December),348-356.

Hirschman, E.C. (1979), "Differences in Consumer Purchase Behavior by Credit Card Payment System," Journal of Conswner Research, 6,58-66

Hirschman, E.C. (1981), "A Comparison of Consumer Payment Systems: Some Strategic Implications,"Joumal of Consumer Research, 3(4), 56-63.

Hirschman, E.C. (1982), "ConsumerPayment Systems: The Relationship of Attribute Structure to Preference and Usage," Joumal ofBusiness, 55(4),531-545.

Hirschman, E.C., Alpert, M.I. and Srivastava, R.K. (1980), "Consumer Credit Card Usage and Retail Purchasing,"Joumal ofRetail Banking, 2(1), 54-66.

Jensen, H.H. and Reynolds, S.W. (1986), "Consumer Credit Use and Age: An Analysis of the Effects of Retirement,"Proceedings of the 32nd Annual Conference ofAmerican Council on Consumer Interests, 262-266.

Lindley, J.T., Rudolph, P., and Selby, E.B., Jr. (1989), "Credit Card Possession and Use: Changes Over Time," Journal of&onomics and Business, 41, 127-142.

Lino, Mark (1989), "Financial Status of Single­Parent Households,"Family Economic Review, 2(1),2-7.

Lino, Mark (1990), "FactorsAffecting Expenditures of Single-Parent Households," Home &onomics Research Journal, 18(3), 191-201.

Mathews, H.L. and Slocum, J.W., Jr. (1969), "Social Class and Commercial Bank Credit Card Usage," Journal ofMarketing, 33,71-78.

Shipp, S. (1988), "How Singles Spend,"American

Demographics, April, 22-27.

Slocum, J.W. and Mathews, H.L. (1970), "Social Class and Income as Indicators of Consumer Credit Behavior," Joumal ofMarketing, 34,69-74.

Soberon-Ferrer, H. and Hatfield-Goldman, J. (1988), "The Effects of Social Class on Consumer Credit Card Repayment Behavior," Proceedings of the 34th Annual Conference ofAmerican Council on Conswner Interests, 325-330.

Sullivan, C.A. and Warden, D.D. (1986), Economics and Demographic Factors Associated with Consumer Debt Use (Working Paper No. 52), West Lafayette, Indiana: Purdue University, Credit Research Center.

Winger, B. J. and Frasca, R. R. (1989), Personal FinIlnce: An Integrated Planning Approach, Columbus, OH: Merrill Publishing Co.

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TABLE 1 Methods of Payment by Gender Difference

Male-Headed Female-Headed

Methods of Payment (0/0) Cash or Check 46.9 49.5 Credit Cards 13.5 15.2 Consumer Loan 39.6 35.3

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TABLE 2. Summary of Descriptive Statistics of the Sample Households

Total Male- Female-Households Headed Headed

Financial Variables ($) (Mean) (Mean) (Mean) Current Income 32,744 35,814 17,037*** Total Financial Assets 25,701 26,894 19,593* Mortgage Debt 13,816 15,354 5,942*** Installment Debt 3,017 3,276 1,691*** Credit Card Debt 372 406 194*** Home ownership (%) 73 76.5 56.7***

Sociodemographic Variables (%) (%) (%) Sex of household head Female 16.4 0.0 100.0 Male 83.7 100.0 0.0

Race of household head White 87.2 88.7 79.2 Nonwhite 12.8 11.3 20.8

Marital status Married 73.4 87.8 0.0 Divorced, widowed,

or Separated 18.2 6.5 78.2 Never married 8.4 5.7 21.8

(Mean) (Mean) (Mean) Age of household head 43.5 43.0 46.1 Education of household head 12.7 12.8 12.4 Household size 3.0 3.1 2.1

Attitude towards credit (%) (%) (%) Negative attitude 21.8 20.7 27.7 Positive attitude 37.2 48.0 43.3

Average expenditure for durable goods $3,576 $3,731 $2,662***

-~ .._-----------_.._--_.._-­

Sample size 1,768 1,479 289

*** significantly different from zero at .01 level ** significantly different from zero at .05 level * significantly different from zero at .10 level

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TABLE 3. Logit Analysis Results for Three Payment Methods by Gender

Cash or Check Credit Cards Consumer Loans Independent Male- Female- Male- Female- Male- Female-Variables Headed Headed Headed Headed Headed Headed

llousehold Income -4.84E-68 -.00001 -4.09E-6 -.00001 -.00002 -.00003 (3.42E-6)b (5.16E-6)** (2.91E-6) (6.3E-6)** (5.40E-6)*** (6.84E6)***

Financial Assets -4.85E-6 -5.77E-6 1.21E-6 -1.64E-6 .00002 .00001 (2.17E-6)** (2.51E-6)** (1.47E-6) (2.19E-6) (4.98E-6)*** (3.95E-6)***

Mortgage Debts -2.76E-6 4.84E-6 3.87E-6 -8.19E-6 -3.43E-6 -1.9E-6 (4.10E-6) (5.24E-6) (5.10E-6) (6.05E-6) (4.48E-6) (6.30E-6)

Installment Debts .0001 .0001 -.00002 .00005 -.00005 -.0002 (.00002)*** (.00003)*** (.00001) (.00004) (.00002)*** (.00003)***

Credit Card Debts .0003 .0006 -.0002 -.0005 -.0002 -.0002 (.0001)*** (.0002)*** (.0001) (.0002)*** (.0001)** (.0001)*

Ilame Ownership -.438 -.791 -.110 .322 .503 .684 (owners) (.197)** (.239)*** (.278) (.311) (.211)** (.256)***

.f:::' Race .080 .453 -.375 .216 .276 -.594 ~ (non-white)

Age (.222) -.019

(.260)* -.017

(.284) -.008

(.351) -.001

(.234) .023

(.267)** .021

Marital status (.006)*** -.356

(.007)** -.097

(.008) -.016

(.009) -.)37

(.007)*** .456

(.008)*** .336

(single) Education

( . 218) -.031

(.. 214) -.015

(.298) -.076

(.293) -.030

(.242)* .052

(.233) .019

( . 028) (.034) (.038)** (.046) (.033) (.038) l-Iousehold Size .068 .117 .074 -.038 -.143 -.136

( .057) (.066)* (.082) (.085) (.061)** (.068)** positive Attitude -.354 .057 .388 .025 .253 -.010

(.197)** ( • 224 ) ( . 300) ( . 308) . (.225) ( . 251) Negative Attitude .376 .228 -.164 -.109 -.425 -.140

(.161)* ( .191) (.223) (.259) (.177)** ( . 209) Purchase Amount .0001 .0001 .0004 .0003 -.0003 -.0002

(.00002)*** (.00003)*** (.00006)***(.00006)*** (.00003)*** (.00003)*** Likelihood ratio

statistic (df=14) 201.31*** 173.71*** 94.16*** 64.16*** 323.61*** 254.27*** l<ho-squared . 14 .17 .12 .10 .23 .25

a= Logit coefficients b= Asymptotic standard error *** significantly different from zero at .01 level ** significantly different from zero at .05 level * significantly different from zero at .10 level

TABLE 4. Results of Gender Difference Test in the Choice of Paynlent Methods

Cash or Check Credit Cards Consumer Loan

Male-headed Households (df=14)

vs. 29.124** 32.362*** 42.742*** Female-headed Households (df= 14)

*** significantly different from zero at .01 level ** significantly different from zero at .05 level

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